Abstract: Provided are techniques including receiving patient data; generating, based on the patient data, a patient risk stratification including: generating stratification scoring based on the patient data; and determining, based on the stratification scoring, a binary classification; generating, based on the patient data, a patient risk level assignment including: generating risk level scoring based on the stratification scoring and the binary classification; and determining, based on the risk level scoring, a risk category; generating a set of patient next best actions including: determining, based on the patient data, a patient outcome prediction; and generating, based on the predictions of patient outcomes, the set of patient next best actions; generating a patient disease state transition prediction including: determining, based on the patient data, a set of transition probabilities; generating, a patient unknown identification prediction including: determining, based on the patient data, a disease propensity sc

Abstract: Product distribution including receiving external conditions data indicative of environmental conditions concerning distribution of products from a point of sale (POS), determining a POS product distribution model for the POS, including first and second product distribution models operable to determine distribution of the first and second products to the POS based on external conditions data, determining, based on application of the external conditions data to the POS product distribution model, a product distribution to the POS, including application of the external conditions data to the first and second product distribution model to determine distributions of the first and second products to the POS, and providing supply instructions for the POS, including first and second product supply instructions to cause the product supply network to provide the distribution of the first and second product to the POS.

Abstract: A method includes receiving historical data housed in the one or more computer systems, the historical data including structured data and unstructured data, storing the historical data in a central database, aggregating the historical data in the central database according to subject matter, validating the aggregated historical data, analyzing the validated aggregated historical data using a series of tools, generating normal profiles in the first computer system from the analyzed validated aggregated historical data, storing the generated normal profiles as horizon data sets, receiving real time data housed in the one or more computer systems, comparing the real time data to the horizon data sets to identify normal and out of normal profiles, and generating rules-based, predictive and interventive outcomes for out of normal profiles based on parameters for investigation.